U.S. patent application number 16/757250 was filed with the patent office on 2020-09-03 for welding system and operating method thereof.
This patent application is currently assigned to LG ELECTRONICS INC.. The applicant listed for this patent is LG ELECTRONICS INC.. Invention is credited to Yonggyu AN, Hojae CHO, Sehui HAN, Kyungmin LEE, Jungsik PARK, Sanggoun SEO, Daeyong SEONG.
Application Number | 20200276674 16/757250 |
Document ID | / |
Family ID | 1000004854812 |
Filed Date | 2020-09-03 |
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United States Patent
Application |
20200276674 |
Kind Code |
A1 |
LEE; Kyungmin ; et
al. |
September 3, 2020 |
WELDING SYSTEM AND OPERATING METHOD THEREOF
Abstract
The present disclosure relates to a welding system which detects
welding defects and repairs the welding defects and the welding
system may include a welding machine configured to weld an object
to be welded, a sensor configured to sense a weldment welded by the
welding machine, and a control device configured to receive first
sensing result data obtained by sensing the weldment from the
sensor, to analyze the weldment based on the first sensing result
data, and to transmit a repair welding command so that the welding
machine performs repair welding based on the analysis result.
Inventors: |
LEE; Kyungmin; (Seoul,
KR) ; SEO; Sanggoun; (Seoul, KR) ; CHO;
Hojae; (Seoul, KR) ; AN; Yonggyu; (Seoul,
KR) ; HAN; Sehui; (Seoul, KR) ; PARK;
Jungsik; (Seoul, KR) ; SEONG; Daeyong; (Seoul,
KR) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
LG ELECTRONICS INC. |
Seoul |
|
KR |
|
|
Assignee: |
LG ELECTRONICS INC.
Seoul
KR
|
Family ID: |
1000004854812 |
Appl. No.: |
16/757250 |
Filed: |
October 17, 2017 |
PCT Filed: |
October 17, 2017 |
PCT NO: |
PCT/KR2017/011465 |
371 Date: |
April 17, 2020 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
B23K 31/125 20130101;
B23K 9/0953 20130101; B23K 26/032 20130101; B23K 26/21 20151001;
B23K 9/0956 20130101 |
International
Class: |
B23K 31/12 20060101
B23K031/12; B23K 26/21 20060101 B23K026/21 |
Claims
1. A welding system comprising: a welding machine configured to
weld an object to be welded; a sensor configured to sense a
weldment on the object welded by the welding machine; and a control
device configured to: receive first sensing result data obtained by
sensing the weldment from the sensor, analyze the weldment based on
the first sensing result data to generate an analysis result, and
transmit a repair welding command to the welding machine for
controlling the welding machine to perform repair welding on the
weldment based on the analysis result.
2. The welding system of claim 1, wherein the control device is
further configured to: control the welding machine to analyze the
weldment to determine a weldment type of the weldment and perform
the repair welding according to the weldment type.
3. The welding system of claim 2, wherein the control device is
further configured to: store weldment determination data obtained
based on mapping a plurality of weldment types with weldment
measurement waveforms and repair welding methods corresponding to
the plurality of weldment types.
4. The welding system of claim 2, wherein the plurality of weldment
types include: a normal weldment type corresponding to a
non-defective weldment, and a plurality of defective weldment types
corresponding to defective weldments, the plurality of defective
weldment types being different from each other according to a
welding defect.
5. The welding system of claim 4, wherein the control device is
further configured to: control the welding machine to perform the
repair welding according to a first repair welding method when the
weldment type is a first defective weldment type, and control the
welding machine to perform the repair welding according to a second
repair welding method when the weldment type is a second defective
weldment type.
6. The welding system of claim 2, wherein the sensor is further
configured to: sense a weldment repair of the weldment and transmit
second sensing result data to the control device, and wherein the
control device is further configured to analyze the weldment repair
based on the second sensing result data.
7. The welding system of claim 1, wherein the welding machine is a
laser welding machine, wherein the sensor is a photodiode, and
wherein the first sensing result data includes an amount of light
measured from the weldment.
8. A control device comprising: a communication interface
configured to: transmit a welding command to a welding machine, and
receive sensing result data obtained by a sensor based on sensing a
weldment on an object welded by the welding machine according to
the welding command; an analyzer configured to analyze the weldment
based on the sensing result data to generate an analysis result;
and a controller configured to: transmit, via the communication
interface, a repair welding command to the welding machine for
controlling the welding machine to perform repair welding on the
weldment based on the analysis result.
9. The control device of claim 8, wherein the controller is further
configured to: analyze the weldment to determine a weldment type,
and control the welding machine to perform the repair welding
according to the weldment type.
10. The control device of claim 8, further comprising: a memory
configured to store weldment determination data obtained based on
mapping a plurality of weldment types with weldment measurement
waveforms and repair welding methods corresponding to the plurality
of weldment types.
11. The control device of claim 8, further comprising: a display
configured to display welding result data corresponding to the
weldment.
12. The control device of claim 8, wherein the controller is
further configured to: control the welding machine to end welding
when the analysis result corresponds to normal welding
corresponding to a non-defective weldment, and control the welding
machine to perform the repair welding when analysis result
corresponds to defective welding.
13. The welding system of claim 1, wherein the sensor is further
configured to sense the weldment in real-time as the weldment is
being welded by the welding machine.
14. The welding system of claim 1, wherein the control device is
further configured to analyze the weldment based on the first
sensing result data in real-time as the weldment is being welded by
the welding machine.
15. The welding system of claim 4, wherein the plurality of
defective weldment types include a burst type defect and a gap type
defect.
16. The welding system of claim 1, wherein the control device is
further configured to analyze the weldment based on characteristic
extraction of the first sensing results data and machine
learning.
17. The welding system of claim 16, wherein the control device is
further configured to: derive a boundary value based extracted
characteristics of the weldment extracted from the first sensing
results, and analyze the weldment based on the boundary value.
18. A method of controlling a welding system, the method
comprising: controlling a welding machine to weld an object; a
sensing, by a sensor, a weldment on the object welded by the
welding machine; receiving, by a control device, first sensing
result data obtained by sensing the weldment from the sensor;
analyzing, by the control device, the weldment based on the first
sensing result data to generate an analysis result; and
transmitting, by the control device, a repair welding command to
the welding machine for controlling the welding machine to perform
repair welding on the weldment based on the analysis result.
19. The method according to claim 18, further comprising:
controlling, by the control device, the welding machine to analyze
the weldment to determine a weldment type of the weldment and
perform the repair welding according to the weldment type.
20. The method according to claim 18, further comprising:
analyzing, by the control device, the weldment based on the first
sensing result data in real-time as the weldment is being welded by
the welding machine.
Description
TECHNICAL FIELD
[0001] The present disclosure relates to a welding system and an
operation method thereof.
BACKGROUND ART
[0002] As a metal joining technique, welding has been applied for a
long time. As a method of heating and melting a metal material and
bonding the metal material to a joining portion, there are arc
welding, gas welding, thermite welding, electron beam welding,
laser welding, robot welding, and the like.
[0003] Welding defects may occur during welding. The welding
defects may mean a phenomenon that causes shape or stress
concentration as a result of welding and a portion that
deteriorates the material and thus damages the strength or
ductility thereof. The welding defects are affected by all
conditions, such as an object to be welded, a welding rod, working
conditions, or the like. For example, as the welding defects, there
are defects generated in the inside of the welding metal such as
angular deformation in which the welding is not straightened and an
angle is formed, defects due to the placement of base materials in
which the members trying to be welded are staggered to misalign,
the slag winding, and the fusion defect, welding cracks, or the
like.
[0004] If welding defects occur excessively, it may be difficult to
achieve the purpose of use of the structure. Therefore, it is
necessary to minimize the occurrence of welding defects in the
welding process, and a method for repairing the welding is
important in a case where a welding defect is generated.
[0005] Conventional welding systems can sense whether a welding
defect occurs. However, the conventional welding system senses only
whether or not a welding defect has occurred, and cannot predict or
discriminate the type of the defect, and if a welding defect
occurs, there is a hassle that the user has to repair the welding
defect by himself.
DISCLOSURE
Technical Problem
[0006] An object of the present disclosure is to provide a welding
system which detects welding defects and performs repair welding of
welding which are detected as defects, and an operating method
thereof.
[0007] An object of the present disclosure is to provide a welding
system which determines the type of welding and automatically
performs repair welding defective welding if welding is defective
welding, and an operating method thereof.
Technical Solution
[0008] A welding system according to an embodiment of the present
disclosure may include a welding machine configured to weld an
object to be welded, a sensor configured to sense a weldment welded
by the welding machine, and a control device configured to receive
first sensing result data obtained by sensing the weldment from the
sensor, to analyze the weldment based on the first sensing result
data, and to transmit a repair welding command so that the welding
machine performs repair welding based on the analysis result.
[0009] The control device may control the welding machine to
analyze the weldment to determine a weldment type and to perform
repair welding according to the weldment type.
[0010] The control device may store weldment determination data
obtained by mapping a plurality of weldment types and a weldment
measurement waveform and a repair welding method corresponding to
each of the plurality of weldment types.
[0011] The weldment types may include a normal weldment type, and a
plurality of defective weldment types which are different from each
other according to welding defect.
[0012] The control device may be configured to control the welding
machine to perform repair welding according to a first repair
welding method if the weldment type is a first defective weldment
type, and control the welding machine to perform repair welding
according to a second repair welding method if the weldment type is
a second defective weldment type.
[0013] The sensor may be configured to sense the repair welded
weldment to transmit a second sensing result data to the control
device, and the control device may be configured to analyze
weldments based on the second sensing result data.
[0014] The welding machine may be a laser welding machine, the
sensor may be a photodiode, and the sensing result data may include
an amount of light measured in the weldment.
[0015] A control device according to an embodiment of the present
disclosure may include a communication interface configured to
transmit a welding command to a welding machine and receive sensing
result data obtained by sensing a weldment welded according to the
welding command from a sensor, an analyzer configured to analyze a
weldment based on the sensing result data, and a controller
configured to control the communication interface to transmit a
repair welding command to the welding machine so that the welding
machine performs repair welding based on the analysis result.
[0016] The controller may be configured to analyze the weldment to
determine a weldment type and control the welding machine to
perform repair welding according to the weldment type.
[0017] The control device may further include a memory that stores
weldment determination data obtained by mapping a plurality of
weldment types and a weldment measurement waveform and a repair
welding method corresponding to each of the plurality of weldment
types.
[0018] The control device may further include a display configured
to display welding result data.
[0019] The controller may control the welding machine to end
welding if the analysis result is determined as normal welding and
to perform repair welding if the analysis result is determined as
defective welding.
Advantageous Effect
[0020] According to an embodiment of the present disclosure, since
welding is performed and repair welding is performed in real-time,
there is no need for an additional process for further checking the
quality after welding, thereby reducing costs.
[0021] According to an embodiment of the present disclosure, by
repeatedly performing repair welding until the welding defect is
removed, there is an advantage that it is possible to provide a
high-quality weldment in a relatively short time and to minimize
leakage defects.
[0022] According to an embodiment of the present disclosure, when
welding is defective welding, the type of a weldment is grasped and
repair welding is performed according to each type, welding defects
can be more completely removed, thereby improving reliability.
DESCRIPTION OF DRAWINGS
[0023] FIG. 1 is a block diagram illustrating a welding system
according to an embodiment of the present disclosure.
[0024] FIG. 2 is a block diagram illustrating a control device
constituting the welding system illustrated in FIG. 1.
[0025] FIG. 3 is a view illustrating a method for controlling a
welding system by a control device according to an embodiment of
the present disclosure.
[0026] FIG. 4 is a ladder diagram illustrating a method for
operating a welding system according to an embodiment of the
present disclosure.
[0027] FIG. 5 is a flowchart illustrating a method for analyzing
sensing result data obtained by sensing a welding result through
characteristic extraction and machine learning according to an
embodiment of the present disclosure.
[0028] FIG. 6 is an exemplary view illustrating weldment
determination data according to an embodiment of the present
disclosure.
[0029] FIG. 7a is an exemplary view illustrating a case where
welding is normally performed.
[0030] FIG. 7b is a first exemplary view illustrating a case where
defective welding is performed.
[0031] FIG. 7c is a second exemplary view illustrating a case where
defective welding is performed.
BEST MODE
[0032] Hereinafter, a specific embodiment of the present disclosure
will be described in detail with the accompanying drawings.
[0033] FIG. 1 is a block diagram illustrating a welding system
according to an embodiment of the present disclosure.
[0034] The welding system according to an embodiment of the present
disclosure may include a welding machine 10, a sensor 20, and a
control device 100.
[0035] Welding is a method of joining to form a direct bond between
solids by applying heat and pressure to the same or different types
of metal materials.
[0036] The welding machine 10 is a device capable of welding a
metal material and may include a laser welding machine, a DC arc
welding machine, an AC arc welding machine, a resistance welding
machine, an ultrasonic welding machine, and the like. The welding
machine 10 may include various types of welding machines, such as a
welding machine of a type that moves and welds along a welding
region of an object to be welded, and a welding machine of a type
welding through angular movement.
[0037] The welding machine 10 may apply heat or pressure to an
object 1 to be welded (see FIG. 3). The welding machine 10 may weld
a metal material by heating or pressing an object 1 to be
welded.
[0038] The sensor 20 may sense the welding result of the welding
machine 10. The sensor 20 may measure whether the welding is
properly sensed by measuring a welded object 1 to be welded. The
sensor 20 may sense a welding defect occurring in the object 1 to
be welded. The sensor 20 may transmit the sensed weldment data to
the control device 100. Here, the weldment data may mean data
obtained by sensing a previously welded weldment.
[0039] The sensor 20 may include an optical sensor such as a
photodiode, a vision sensor, a thermal image sensor, an
ultra-high-speed camera, a displacement sensor, a pressure sensor,
an acceleration sensor, an acoustic sensor, or the like.
[0040] The control device 100 may control the welding machine 10
and the sensor 20. Specifically, the control device 100 may control
the welding machine 10 to weld the object 1 to be welded and
perform repair welding thereof. In addition, the control device 100
may receive weldment data from the sensor 20. The control device
100 may determine whether a welding defect occurs, whether repair
welding is performed, or the like based on the received weldment
data.
[0041] FIG. 2 is a block diagram illustrating a control device
constituting the welding system illustrated in FIG. 1.
[0042] The control device 100 according to an embodiment of the
present disclosure may include at least one of a communication
interface 110, an analyzer 120, a memory 130, a display 140, the
input 150, and the controller 160. In other words, the components
listed above are merely examples for the description of the present
disclosure, and, according to an embodiment, the control device 100
may omit some of the components listed above or further include
additional components.
[0043] The communication interface 110 may transmit a welding
command to the welding machine 10. The welding command may include
a welding command for the entire object to be welded, a welding
command for a portion of the object to be welded, and a repair
welding command. The communication interface 110 may transmit a
welding command which controls the welding machine 10 to perform
welding start, welding end, or the like. The communication
interface 110 may transmit a welding command including data
regarding a welding method to the welding machine 10.
[0044] The communication interface 110 may transmit a sensing
command which controls the sensor 20 to sense the object 1 to be
welded. The sensor 20 may sense the object 1 to be welded according
to a sensing command received from the communication interface 110
of the control device 100. For example, the communication interface
110 may transmit a sensing command which controls to sense the
object 1 to be welded while the welding machine 10 welds the object
1 to be welded.
[0045] The communication interface 110 may receive the weldment
data obtained by sensing the object 1 to be welded from the sensor
20. For example, when the sensor 20 is a photodiode, the
communication interface 110 may receive weldment data including the
amount of light for each region of the object 1 to be welded.
[0046] The analyzer 120 may analyze data related to the object 1 to
be welded, weldment data obtained by sensing the welding result,
and the like. The analyzer 120 may analyze data related to the
object 1 to be welded to determine a welding method, a heat amount
or pressure applied during welding, and the like. The analyzer 120
may analyze the weldment data to determine welding quality, a
weldment type, whether to perform re-welding, and the like.
However, the above-described determination information is merely
exemplary for the explanation, and the analyzer 120 may determine
and obtain information necessary for welding based on various data
related to welding.
[0047] The memory 130 may store at least one or more data necessary
for welding. According to an embodiment of the present disclosure,
the memory 130 may store weldment determination data. Here, the
weldment determination data may be data obtained by mapping a
weldment type according to the weldment data sensed through the
sensor 20 and a repair welding method corresponding to each
weldment type. The analyzer 120 may analyze the weldment data based
on the weldment determination data stored in the memory 130. In
other words, the analyzer 120 may determine a weldment defective
type of the weldment based on the weld determination data and
obtain a repair welding method according to the determined weldment
defective type. The detailed description of the weldment
determination data will be described later with reference to FIG.
6.
[0048] The display 140 may display welding result data based on the
weldment data. Here, the welding result data may mean data related
to a previously completed weldment. For example, the welding result
data may include at least one of an image of a weldment in which
welding is performed, welding quality, a weldment type, and a
repair welding method.
[0049] The input 150 may receive an input command related to
welding. The user may input a command related to welding through
the input 150. For example, the input 150 may receive a start/end
command for welding, a command for selecting a welding method, an
execution command for repair welding, and the like.
[0050] The controller 160 may control the overall operation of the
control device 100. The controller 160 may control each component
constituting the control device 100. In other words, the controller
160 may control the communication interface 110, the analyzer 120,
the memory 130, the display 140, and the input 150.
[0051] In addition, the controller 160 may control the
communication interface 110 to control the welding system. In other
words, the controller 160 may control the welding machine 10 and
the sensor 20 through the communication interface 110.
[0052] Next, FIG. 3 is a view illustrating a method for controlling
a welding system by a control device according to an embodiment of
the present disclosure.
[0053] First, the control device 100 may transmit a welding command
which controls to weld the object 1 to be welded to the welding
machine 10 and transmit a sensing command which controls to sense
the weldment to the sensor 20. At this time, the weldment may mean
a portion or all of the object 1 to be welded on which welding is
performed.
[0054] The sensor 20 may be positioned adjacent to the welding
machine 10 to sense the weldment in near real-time. For example,
when the welding machine 10 is a laser welding machine, the sensor
20 may be located at the head of the laser welding machine.
However, since this is only an example, it is reasonable that the
location of the sensor 20 is not limited.
[0055] The welding machine 10 may be welded by heating or pressing
the object 1 to be welded according to a welding command received
from the control device 100.
[0056] The sensor 20 may sense a weldment according to a sensing
command received from the control device 100. For example, the
sensing command may be a command for sensing the welding result in
real-time. In this case, the sensor 20 may sense in real-time along
the welding region welded by the welding machine 10.
[0057] The sensor 20 may transmit weldment data obtained by sensing
the weldment to the control device 100. The control device 100 may
receive the weldment data and monitor and analyze the welding
results. The control device 100 may transmit a repair welding
command to the welding machine 10 according to the analysis
result.
[0058] FIG. 4 is a ladder diagram illustrating a method for
operating a welding system according to an embodiment of the
present disclosure.
[0059] The communication interface 110 of the control device 100
may transmit a welding command to the welding machine 10 (S10). The
welding command is the same as described above.
[0060] The communication interface 110 of the control device 100
may transmit a sensing command to the sensor 20 (S11). The sensing
command is also the same as described above.
[0061] The welding machine 10 may weld the object 1 to be welded
according to a welding command (S13).
[0062] The welding machine 10 may weld all or a portion of the
object 1 to be welded by a welding command. Meanwhile, the order of
step S11 in which the control device 100 transmits a sensing
command to the sensor 20 and step S13 in which the welding machine
10 welds an object to be welded may be changed.
[0063] The sensor 20 may sense the welded weldment according to the
received sensing command (S15).
[0064] According to one embodiment, the sensor 20 may sense the
weldment while the welding machine 10 welds the object 1 to be
welded. In other words, the sensor 20 may immediately sense a
region of the object 1 to be welded which is performing welding or
a region of the object 1 to be welded in which welding is
performed, to sense the weldment in near real-time.
[0065] According to another embodiment, the sensor 20 may sense a
weldment after the welding machine 10 completes welding.
[0066] The sensor 20 may sense the weldment in real-time based on
the data included in the sensing command or may sense the weldment
after welding is completed.
[0067] The sensor 20 may obtain sensing result data as the object
to be welded is sensed. For example, the sensor 20 may be a
photodiode sensor, and the photodiode sensor may obtain sensing
result data including light amount information for a weldment.
[0068] The sensor 20 may transmit the obtained sensing result data
to the control device 100 (S17).
[0069] The communication interface 110 of the control device 100
may receive sensing result data from the sensor 20. The controller
160 may analyze the received sensing result data (S19).
[0070] According to an embodiment, the controller 160 of the
control device 100 may output the measurement waveform and analyze
the sensing result data. For example, the sensing result data may
include light amount information, and the light amount information
may be an analog signal indicating the light amount. The analyzer
120 of the control device 100 may convert an analog signal
representing light amount information into a digital signal, and
then output a measurement waveform based on the converted digital
signal. The controller 160 of the control device 100 may analyze
the welding result based on the output measurement waveform.
[0071] According to another embodiment, the controller 160 of the
control device 100 may analyze the sensing result data through
characteristic extraction and machine learning. Next, referring to
FIG. 5, a method of analyzing sensing result data obtained by
sensing a welding result through characteristic extraction and
machine learning according to an embodiment of the present
disclosure will be described.
[0072] FIG. 5 is a flowchart illustrating a method for analyzing
sensing result data obtained by sensing a welding result through
characteristic extraction and machine learning according to an
embodiment of the present disclosure.
[0073] The communication interface 110 of the control device 100
may receive the sensing result data (S101).
[0074] The analyzer 120 of the control device 100 may obtain the
sensing result data through the communication interface 110
(S103).
[0075] The analyzer 120 may analyze/convert the sensing result data
(S105).
[0076] For example, the analyzer 120 may convert an analog signal
representing the light amount into a digital signal and output a
measurement waveform.
[0077] The analyzer 120 may extract characteristics of the
analyzed/converted data (S107) and derive a boundary value
(S109).
[0078] Steps S105 to S109 are methods for extracting the
characteristics of the sensing result data and are also applicable
to the embodiment of outputting the measurement waveform described
above.
[0079] The analyzer 120 may calculate the sensing result data
(S111).
[0080] The analyzer 120 may remove the outlier from the calculated
sensing result data (S113).
[0081] The analyzer 120 may remove the outliers from the calculated
sensing result data and learn/calculate the data with the outliers
removed (S115).
[0082] In addition, the analyzer 120 may apply the data with the
outliers removed to the statistical optimization algorithm (S117).
After applying to the statistical optimization algorithm, the
analyzer 120 may calculate the sensing result data again (S111) and
repeat the step of removing outliers. In addition, the analyzer 120
may learn/compute data after applying a statistical optimization
algorithm (S115).
[0083] Steps S111 to S117 are methods for statistically optimizing
to accumulate previously extracted characteristics to improve the
reliability of sensing result data analysis.
[0084] The analyzer 120 may determine whether it is good or bad
based on the calculated data (S119).
[0085] In other words, the analyzer 120 may determine the quality
of the sensing result based on the calculated data.
[0086] The analyzer 120 may finally determine by applying weight
(S121).
[0087] The analyzer 120 may analyze the sensing result data in a
method as illustrated in FIG. 5. However, since the method
illustrated in FIG. 5 is merely exemplary, the method needs not to
be limited thereto.
[0088] Again, FIG. 4 will be described.
[0089] The analyzer 120 may determine the weldment type based on
the analysis result of the sensing result data (S21).
[0090] The control device 100 may obtain the shape and size of a
welding defect or the like as a result of analyzing the sensing
result data and may obtain a weldment type.
[0091] Here, the weld type may include a type indicating a normal
weldment in which the welding is normally performed, and a type
indicating a defective weldment in which the welding is abnormally
performed, and the type representing a defective weldment may
include at least one defective weldment type which is different
according to the welding defect.
[0092] The analyzer 120 may determine whether the weldment welded
by the welding machine 10 is a normal weldment or a defective
weldment based on the analysis result of the sensing result data,
and determine what kind of defective weldment in a case of a
defective weldment.
[0093] Here, the defective weldment may indicate a weldment in
which at least one welding defect is generated as a result of
welding to an object to be welded. At this time, the types of
welding defects generated in the defective weldment may vary. For
example, the weldment may be welded abnormally as a burst occurs,
or a gap may be generated and the weldment may be welded
abnormally. However, this is merely exemplary, and the causes of
abnormal welding may vary.
[0094] According to the type of welding defect, the shape, the
size, or the like of the weldment may be different. Therefore, it
is advantageous to improve the reliability since welding defects
can be more completely eliminated if the type of the defective
weldment is grasped and repair welding is performed according to
each type.
[0095] The analyzer 120 may determine the weldment type by
obtaining data obtained by matching the analysis result of the
sensing result data from the weldment determination data stored in
the memory 130.
[0096] Next, referring to FIGS. 6 and 7a to 7c, a method for
determining weldment determination data and a weldment type will be
described.
[0097] FIG. 6 is an exemplary view illustrating weldment
determination data according to an embodiment of the present
disclosure.
[0098] The memory 130 may store weldment determination data. The
weldment determination data may include data obtained by mapping
the weldment type, a measurement waveform, and a repair welding
method.
[0099] Referring to the example illustrated in FIG. 6, when welding
is performed normally, the weldment type indicates Type 1, the
measurement waveform illustrates a relatively uniform size, and the
repair welding method may be A1. When welding is performed
abnormally by bursting, the weldment type indicates Type 2, the
measurement waveform indicates a relatively uniform size and then
indicates a peak at a point, and the repair welding method may be
B2. When welding is performed abnormally due to a gap, the weldment
type indicates Type 3, the measurement waveform indicates a
non-uniform size, and the repair welding method may be B3.
[0100] At this time, each of the repair welding methods A1, B1, and
B2 may be a defect removal method according to each defect cause.
The mapped repair welding method and the weldment type indicating a
normally welded case may be a method that does not perform repair
welding.
[0101] Meanwhile, the expressions of Type 1, Type 2, Type 3, and
the like indicating the weldment type, and A1, B2, B3, and the like
indicating the repair welding method are merely illustrative for
convenience of explanation, and the weldment determination data can
be expressed as each type of the weldment and each of the repair
welding methods in various ways.
[0102] Similarly, the measurement waveform may be different from
the example illustrated in FIG. 6 according to the type of the
welding machine 10 and the sensor 20. The measurement waveform
illustrated in FIG. 6 is merely an example of the measurement
waveform when the welding machine 10 is a laser welding machine and
the sensor 20 is a photodiode sensor.
[0103] Specifically, FIG. 7a is an exemplary view illustrating a
case where welding is normally performed.
[0104] The welding machine 10 may apply heat or pressure to the
object 1 to be welded. Reference numeral 11 indicates a
visualization of heat or pressure applied by the welding machine
10. If the welding machine 10 is a laser welding machine, reference
numeral 11 may indicate a laser beam. When heat or pressure applied
by the welding machine 10 forms a stable molten pool 2, welding may
be normally performed. Therefore, when normal welding is performed,
since the molten pool 2 is stably formed and the amount of light
measured by the sensor 20 is constant, the measurement waveform may
indicate a uniform size.
[0105] FIG. 7b is a first exemplary view illustrating a case where
welding is performed abnormally.
[0106] A burst may occur due to heat or pressure applied by the
welding machine 10. When the burst occurs, a large amount of
spatter 3 is generated, and abnormal welding may be performed.
Here, the spatter 3 may represent slags or metal particles
scattered during welding. Therefore, when welding is performed
abnormally due to bursting, the surface area of the light amount
measurement object increases due to a large amount of spatters 3,
and the distance between the spatters 3 and the sensors 2
decreases, so that the amount of light measured by the sensor 2 can
relatively increase. In this case, the amount of light measured by
the sensor 2 may indicate a uniform size and suddenly increase at
the point where the burst occurs.
[0107] FIG. 7c is a second exemplary view illustrating a case where
welding is performed abnormally.
[0108] A gap 4 may be generated in the object 1 to be welded to
weld. When welding is performed abnormally due to the gap 4, the
irradiated laser beam may be scattered, and reference numeral 12
may indicate the scattered beam. Therefore, when the welding is
performed abnormally due to the gap, a signal size difference due
to a change in the welding distance may occur, and a large number
of signal peaks may occur due to the scattering of the beam. In
this case, the amount of light measured by the sensor 2 has a large
number of peaks and may indicate a non-uniform size.
[0109] As described above, the control device 100 according to an
embodiment of the present disclosure may store a measurement
waveform according to a cause of a defect, and a weldment type and
a repair welding method corresponding to each measurement waveform.
The control device 100 may analyze the sensing result data to
determine the type of the weldment, and the sensing result data may
be a measurement waveform obtained by analyzing the sensing result
data received from the sensor 20. According to an embodiment, the
measurement waveform may indicate the amount of light.
[0110] Again, FIG. 4 will be described.
[0111] The controller 160 of the control device 100 may determine
whether the welding is defective (S23).
[0112] As a result of determining the weldment type, the controller
160 may determine whether the weldment is a normal weldment or a
defective weldment. The controller 160 may determine that if the
welding type is normal, the weldment is normal welding, and if the
welding type is abnormal, the weldment is welding defect.
[0113] In a case of normal welding, the controller 160 may display
welding result data (S33). Alternatively, the controller 160 may
end welding in a case of normal welding. According to an
embodiment, the step of displaying the welding result data may be
omitted.
[0114] If the welding is defective, the controller 160 may display
welding result data (S25).
[0115] Here, the welding result data is the same as described
above. The display 140 may display at least one of an image of the
weldment in which the welding is performed, welding quality, a
welded type, and a repair welding method.
[0116] According to an embodiment, as illustrated in FIG. 4, the
controller 160 may display welding result data before performing
repair welding and also display welding result data after
performing repair welding.
[0117] According to another embodiment, the controller 160 may
display the welding result data only after performing the repair
welding, by omitting the step of displaying the welding result data
before performing repair welding.
[0118] The controller 160 may determine whether re-welding is
necessary (S27).
[0119] According to an embodiment, the controller 160 may
automatically determine whether re-welding is necessary based on
the type of the weldment. For example, the controller 160 may
determine that re-welding is necessary when the weldment type is
abnormal welding.
[0120] According to another embodiment, the controller 160 may
receive a repair welding execution command through the input 150
and determine whether re-welding is necessary according to the
repair welding execution command. For example, the controller 170
may determine that re-welding is necessary when the input 150
receives a repair welding execution command and may determine that
re-welding is not necessary when the repair welding execution
command is not received.
[0121] If it is determined that re-welding is not necessary, the
controller 160 may display the welding result data (S33).
[0122] If it is determined that re-welding is necessary, the
controller 160 may transmit a repair welding command to the welding
machine 10 (S29) and transmit a repair welding sensing command to
the sensor 20.
[0123] The welding machine 10 may perform repair welding of the
object to be welded according to the weldment type (S31).
[0124] Next, a method for performing repair welding by the welding
machine 10 according to various embodiments of the present
disclosure will be described.
[0125] According to the first embodiment of the present disclosure,
the welding machine 10 may perform repair welding based on a
pre-stored database. For example, the welding machine 10 may
perform repair welding by obtaining a repair welding method
corresponding to a weldment type based on the weldment
determination data as described above. In other words, the control
device 100 transmits a repair welding method that maps to a
weldment type based on the weldment determination data to the
welding machine 10, and the welding machine 10 can perform repair
welding according to the received repair welding method.
Alternatively, since the database for the repair welding method is
stored in the welding machine 10, the repair welding method
corresponding to the received weldment type can be obtained from
the pre-stored database to perform repair welding.
[0126] According to the second embodiment of the present
disclosure, the welding machine 10 may repair and weld the weld
defective region while re-welding the entire weldment. As described
above, in a case where the welding machine performs repair welding
while re-welding the entire weldment, the welding machine 10 can
also repair small welding defects together, thereby further
improving the quality of the entire weldment.
[0127] According to the third embodiment of the present disclosure,
the welding machine 10 may perform repair welding of only a partial
region corresponding to a welding defect. The welding machine 10
may obtain the size, the location information, and the like of a
welding defect from the control device 100. The welding command
received from the control device 100 may include size, location
information, and the like of a welding defect. The welding machine
10 may perform repair welding so that only the welding defect is
removed, based on the obtained size and location information of the
welding defect. At this time, the welding machine 10 can perform
repair welding of only the location of the welding defect.
Alternatively, the welding machine 10 may perform repair welding of
a predetermined region including the location of the welding
defect. For example, the welding machine 10 may perform repair
welding up to +/-1 mm region of the location of the welding
defect.
[0128] The welding machine 10 may perform repair welding according
to any one of the various embodiments described above.
[0129] The sensor 20 may sense the repair welded weldment
(S33).
[0130] A method for sensing the repair welded weldment may be the
same as the method for sensing the welded weldment described in
step S15.
[0131] The sensor 20 may transmit sensing result data obtained by
sensing for repair welding to the control device 100 (S34).
[0132] The control device 100 may repeat steps S19 to S35 described
above.
[0133] The welding system according to an embodiment of the present
disclosure can repeatedly perform repair welding when welding
defects occur while performing welding, thereby providing a
high-quality weldment in a short time and minimizing leakage
defects.
[0134] In addition, the welding system according to an embodiment
of the present disclosure has the advantage of performing repair
welding in real-time while performing welding. Accordingly, there
is no need for an additional process to check the quality after
welding, and there is an effect of cost reduction due to reduced
investment cost.
[0135] In addition, the welding system according to an embodiment
of the present disclosure not only performs quality determination
and repair welding by using the existing database, but also can
additionally secure and learn mass production data, and thus there
is an advantage that initial defect leakage is prevented,
monitoring hit ratio through learning increases, and reliability is
improved.
[0136] As described above, the welding system according to the
embodiment of the present disclosure can be applied to laser
welding of Al and Cu materials for electric vehicle batteries,
manufacturing methods such as different combinations such as Al and
Cu, Al compression, and Al die casting is also applied to welding
by different combinations and thus welding defect can be detected
and repair welding through feedback control can be performed.
[0137] According to an embodiment of the present disclosure, it is
possible to implement the above-described method as code readable
by a processor on a medium on which a program is recorded. Examples
of the medium readable by the processor include ROM, RAM, CD-ROM,
magnetic tape, floppy disk, and optical data storage device.
[0138] The above description is merely illustrative of the
technical idea of the present disclosure, and those skilled in the
art to which the present disclosure pertains may make various
modifications and variations without departing from the essential
characteristics of the present disclosure. The welding system
described above is not limited to the configuration and method of
the above-described embodiments, and the above-described
embodiments may be configured by selectively combining all or part
of each embodiment so that various modifications can be made.
[0139] Therefore, the embodiments disclosed in the present
disclosure are not intended to limit the technical spirit of the
present disclosure, but to explain, and the scope of the technical
spirit of the present disclosure is not limited by these
embodiments.
[0140] The scope of protection of the present disclosure should be
interpreted by the claims below, and all technical spirits within
the scope equivalent thereto should be interpreted as being
included in the scope of the present disclosure.
* * * * *